HHU at SemEval-2023 Task 3: An Adapter-based Approach for News Genre Classification

被引：0
|
作者：
Billert, Fabian [1 ]
Conrad, Stefan [1 ]
机构：
[1] Heinrich Heine Univ Dusseldorf, Dusseldorf, Germany
来源：
17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023 | 2023年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes our approach for Subtask 1 of Task 3 at SemEval-2023. In this subtask, task participants were asked to classify multilingual news articles for one of three classes: Reporting, Opinion Piece or Satire. By training an AdapterFusion layer composing the task-adapters from different languages, we successfully combine the language-exclusive knowledge and show that this improves the results in nearly all cases, including in zero-shot scenarios.
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页码：1166 / 1171
页数：6
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